A feedforward neural
network is a
directed acyclic graph, a network with two or more
layers of
nodes in which the
signals travel unidirectionally, always from a layer to the next highest layer. If the network is fully
connected, each
node in a given
layer has a
weight connecting it to every
node in the next
layer. It is
unusual and much more
complicated to train a network if a node can be connected to a node that is not in the immediately succeeding layer.
Fully connected feedforward neural networks are useful for pattern classification and are often trained using the error backpropagation algorithm.